With the continuous development of Internet technologies, search engines mostly tend to become more and more personalized and intellectualized. Basically, personalized search improves the search efficiency for a user by tracing and analyzing search behaviors of the user while intellectualized search mainly comprehends and analyzes information of search demands by a search engine, and utilizes the self-adaptive ability and the self-adjusting ability of the search engine to provide more satisfactory search results for the user. However, the existing search engines, which mainly apply a keyword as the retrieval basis, complete the retrieval process by retrieving a webpage indexing database and returning the results. This method has very apparent limitations. The keyword technique can hardly express the retrieval intention of the user clearly, and the search engines fail to better comprehend the input information of natural languages, e.g., if a user wants to learn the composition of the Android framework, the intention of the user cannot be expressed clearly even if “Android framework” or “framework composition” etc. is inputted. If the user inputs “composition of the Android framework” which clearly expresses, however, the search engine will only return related websites associated with such keyword as “Android”, “framework” or “composition” etc. On the other hand, typically, millions of documents will be returned by querying one or several simple keywords. In this case, the user can hardly find the necessary information which the user is interested in. In order to solve these limitations, currently there are extensive researches, one of which is meta-search engine. A meta-search engine, like a filter channel, takes the output results of independent search engines as input, rearranges the output results by meta-search techniques such as integration, invocation, control and optimization etc., and presents the final results to the user to provide a real-time response for the user.
At present, personalized search services based on the interest of the user have not been realized in the field of mobile terminals. Taking the open-source mobile phone operation system Android platform issued by Google as an example, searching is basically realized by directly invoking the search engine in the browser. In order to facilitate searching, the search suggestion technique of Google is used largely, which mainly provides the most popular correlated search suggestions, as well as the history search suggestions etc. queried by the user. However, personalized search schemes has not been realized based on the characteristics that a mobile terminal is used by a specific user generally, and that a great amount of data which the user is interested in is included in each mobile terminal.